Prostate cancer is typically characterized by complex inter- and intra-tumor heterogeneity. This level of complexity remains difficult to address effectively by clinical treatments and is one of the main reasons for treatment failure. To date, studies focused on the heterogeneity of prostate tumors have been largely limited to defining specific cellular subtypes and identifying genomic alterations. While these studies have revealed that intra-tumor heterogeneity is complex at the cellular and genomic levels, they have failed to define the underlying growth dynamics adopted by the genetically diverse cell subpopulations (clones) comprising the tumor. Advances in understanding this issue would be extremely beneficial for identifying metastatic and drug- resistant cell subpopulations and designing targeted therapies. In this application, I propose to study the origin of heterogeneity in prostate cancer from the perspective of evolutionary biology. Specifically, I will investigate the evolution of prostate cancer by delineating the kinetics of clonal growth in genetically-engineered mouse models. My preliminary studies indicate that the cellular dynamics displayed by prostate stem cells and their progeny during androgen-dependent tissue regeneration can serve as a basis for understanding tumor evolution. Using an inducible multi-color reporter in lineage- tracing studies, I have shown that prostate tumors undergo clonal reduction during tumor progression, in which aggressive, fast-growing clones become rapidly dominant. Based on these results, I hypothesize that prostate cancers are hierarchically organized multi-clonal tumors and undergo androgen-dependent clonal selection. I will investigate this hypothesis using three specific aims: (1) Investigation of the clonal evolution of prostate epithelial stem cells during androgen-mediated regeneration by lineage-tracing analyses of the clonal fate of prostate stem cells using a multi-color reporter; (2) Analyss of transformed prostate stem cells during clonal selection in tumors by investigating the clonal size and distribution of transformed castration-resistant prostate epithelial stem cells; and (3) Investigation of the clonal fate of luminal epithelial cells during malignant transformation by multi-color lineage-tracing of terminally-differentiated luminal cells during prostate tumorigenesis. I will use innovative computational methodologies to integrate the clonal data obtained in these analyses to characterize the modes of homeostatic and malignant growth adopted by prostate cells. Taken together, these studies will provide an evolutionary basis for modeling prostate cancer dynamics and will have important translational implications for personalized therapies and may lead to identification of novel therapeutic targets.